The Theory And Applying Research Of Landslide Exterior Monitoring System Based On The Integration Of GPS And GIS

Landslide is one of the most serious geological disasters. In recent years, more and more large-scale foundational establishments have been brought into effect, such as expressways, railways, reservoirs, etc. These engineerings often involve digging mountains, which may result in landslide. There are large numbers of landslides, so a lower cost, more popular, and effective monitoring method is needed to monitor these latent or generant landslide, and to avoid inestimable loss. Landslide monitoring is using all kinds of methods to forecast the trend of landslide, and provide basis and estimate for landslide father.The GPS technology has many advantages, such as round-the-clock, roboticized, liberty in selecting points, and capable of providing three-dimensional coordinates, so it provides a new and effective data collection method for landslide monitoring. Because of the strong space analyzing function and space database function, GIS technology is very useful to solve many problems in the landslide monitoring field.The author mainly research exterior deformation laws of landslide, and theory of establishment of GPS monitoring net and data processing. According to the data processing of a landslide in Sanxia, the author adopt a model based on statistical hypothesis testing and mean spacing method, and do exterior deformation analysis, and use GIS technology to classify and administer the information of GPS landslide monitoring. According to research the administering mode of GPS monitoring data using GIS technology, the author ascertain a best scheme and math model for landslide exterior monitoring system based on the integration of GPS and GIS, and establish a system structure using Visual Basic 6.0 and MapObjects 2.3, and develop a data processing, analyzing and administratoring software—Landslide Exterior Monitoring System(LEMS1.0) based on the integration of GPS and GIS at last, which automatize and intelligentize data analyzing and processing of landslide monitoring, and provide accurate and effective basis for landslide forcasting.